Oops, you're using an old version of your browser so some of the features on this page may not be displaying properly.

MINIMAL Requirements: Google Chrome 24+Mozilla Firefox 20+Internet Explorer 11Opera 15–18Apple Safari 7SeaMonkey 2.15-2.23

Poster Display session 2

4631 - Multi-Gene Prognostic Signatures and Prediction of Pathological Complete Response of ER-Positive HER2-Negative Breast Cancer Patients to Neo-Adjuvant Chemotherapy

Date

29 Sep 2019

Session

Poster Display session 2

Topics

Breast Cancer

Presenters

Claudia Mazo

Citation

Annals of Oncology (2019) 30 (suppl_5): v55-v98. 10.1093/annonc/mdz240

Authors

C. Mazo1, S. Barron2, C. Mooney3, W.M. Gallagher2

Author affiliations

  • 1 Ucd School Of Computer Science, University College Dublin, 4 - Dublin/IE
  • 2 -, OncoMark Limited, 4 - Dublin/IE
  • 3 Ucd School Of Computer Science, University College Dublin, Dublin/IE
More

Resources

Abstract 4631

Background

Determining which early stage breast cancer patients should receive chemotherapy is an important clinical and economic issue. Chemotherapy has many adverse side effects, impacting on quality of life, along with significant economic consequences. Biomarkers that can predict patient response to chemotherapy can help avoid ineffective overtreatment. The aim of this work is to assess if the OncoMasTR (OM) signature can predict pathological complete response (pCR) to neo-adjuvant chemotherapy, and to compare its predictive value with EndoPredict (EP) and Oncotype DX (RS).

Methods

Gene expression datasets derived from breast cancer patients that had pre-treatment biopsies, received neo-adjuvant chemotherapy and an assessment of pCR were obtained from GEO (GSE16716, GSE20271, GSE25066, GSE32646, GSE34138, GSE41998, GSE22226). Patients with ER-positive, HER2-negative disease and pCR data were selected. OM, EP and RS numeric risk scores were approximated by applying the gene coefficients to the corresponding mean probe expression values. Association with pCR was estimated using logistic regression.

Results

A total of 813 patients with 66 pCR events were included in the analysis. OM, EP and RS prognostic scores were moderately well correlated according to the Pearson’s correlation coefficient: OM vs EP (min=0.44; mean=0.67; max=0.81), OM vs RS (min=0.34; mean=0.62; max=0.79), and RS vs EP (min=0.55; mean=0.79; max=0.89). Significant predictors of pCR with p-values of 0.0001 for all three signatures. Odds ratios for a 1 standard deviation increase in risk score, adjusted for cohort, were similar in magnitude and not significantly different: OM 1.66 (1.29 to 2.16), EP 1.76 (1.37 to 2.27), RS 1.84 (1.44 to 2.35).

Conclusions

In this in silico analysis, OM, EP and RS prognostic scores were significantly predictive of pCR to neo-adjuvant chemotherapy in ER-positive, HER2-negative breast cancer. Optimal stratification for neo-adjuvant chemotherapy offers the opportunity for personalised care, improved therapy response rates, and reduced ineffective treatment and costs.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

University College Dublin.

Funding

The EI and from the European Union’s Horizon 2020 research and innovation programme under the Marie Slodowska-Curie grant agreement No. 713654.

Disclosure

The author has declared no conflicts of interest.

This site uses cookies. Some of these cookies are essential, while others help us improve your experience by providing insights into how the site is being used.

For more detailed information on the cookies we use, please check our Privacy Policy.

Customise settings
  • Necessary cookies enable core functionality. The website cannot function properly without these cookies, and you can only disable them by changing your browser preferences.